Design and Implementation of Artificial Intelligence and Machine Learning Techniques for Security of Healthcare Systems
N. Raju · 2024
The aim of this research is to examine the use of Artificial Intelligence (AI) an Machine Learning (ML) methods for the security of healthcare systems. Starting with the historical background and works in this area, the research examines methods like anomaly detection, patterns and signs emergence, and risk prediction methods that are suitable to detect and prevent them. By providing a comprehensive overview of the machine learning algorithms like neural networks, decision trees, and clustering, the research proves that these technologies efficiently enhance the defense mechanisms of the healthcare system against cyber threats. Measurement indices which include Accuracy, Precision, Recall, F1-Score among others are tested on benchmarking scenarios which gives the researcher an understanding of the strengths as well as the weaknesses of these methodologies. It also incorporates comparative assessments with wellestablished reference techniques highlighting the need to integrate strong security protocols and advanced contingency plans for securing patients’ enclosed and critical health information and healthcare IT networks from emerging cyber threats.